Paper Citation Record · LEDGER

End-to-end symbolic regression with transformers

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2204.10532.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2204.10532 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:08:03.605824Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-19T20:07:44.748607Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 399bae0b-f363-43d4-b240-e3a577c30f24 · inbound

DisCo-DSO: Coupling Discrete and Continuous Optimization for Efficient Generative Design in Hybrid Spaces cites this paper.

DisCo-DSO: Coupling Discrete and Continuous Optimization for Efficient Generative Design in Hybrid Spaces End-to-end symbolic regression with transformers

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-11T15:29:37.044198Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d4b7744c-e69c-4190-b7b8-bbc843f8379d · inbound

SyMANTIC: An Efficient Symbolic Regression Method for Interpretable and Parsimonious Model Discovery in Science and Beyond cites this paper.

SyMANTIC: An Efficient Symbolic Regression Method for Interpretable and Parsimonious Model Discovery in Science and Beyond End-to-end symbolic regression with transformers

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-09T05:02:19.783885Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 93235bc6-ab38-4680-a1f3-c03080d7c51e · inbound

Learning Semantics-aware Search Operators for Genetic Programming cites this paper.

Learning Semantics-aware Search Operators for Genetic Programming End-to-end symbolic regression with transformers

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-08T22:21:02.160761Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f38e303e-c68b-4d0b-99be-33779eaa643d · inbound

Deep Symbolic Optimization: Reinforcement Learning for Symbolic Mathematics cites this paper.

Deep Symbolic Optimization: Reinforcement Learning for Symbolic Mathematics End-to-end symbolic regression with transformers

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-15T21:08:03.605824Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 82690a55-3530-48a5-a761-4258c280d678 · inbound

LLM-Based Scientific Equation Discovery via Physics-Informed Token-Regularized Policy Optimization cites this paper.

LLM-Based Scientific Equation Discovery via Physics-Informed Token-Regularized Policy Optimization End-to-end symbolic regression with transformers

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-03T01:09:51.893983Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 64700f01-355f-445e-916c-097ee1da2629 · inbound

Discovering interpretable low-dimensional dynamics using maximum entropy cites this paper.

Discovering interpretable low-dimensional dynamics using maximum entropy End-to-end symbolic regression with transformers

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-19T20:07:44.750940Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 08e33425-27a3-46d4-bd48-a7d4f6bc631d · inbound

MOT-SR: Multi-Objective Tool-Augmented Scientific Equation Discovery with Large Language Models cites this paper.

MOT-SR: Multi-Objective Tool-Augmented Scientific Equation Discovery with Large Language Models End-to-end symbolic regression with transformers

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-03T04:39:25.868155Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.